A method for deriving monthly runoff series in data - scarce regions

Abstract

The present invention discloses a method for deriving the monthly runoff series in an area without data, which relates to the field of hydrological runoff design. By selecting a reference station basin, sorting out the rainfall-runoff series of the reference station basin, establishing a runoff generation model for the reference station basin, fitting the parameters of the runoff generation model for the reference station basin, and using the parameters of the runoff generation model fitted for the reference station basin and the monthly precipitation of the design basin, the monthly runoff series of the design basin is calculated. This method requires less data and can derive the monthly runoff series in areas with only monthly rainfall data, which has certain practical significance for areas lacking data.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrological runoff process simulation, and particularly to a method for deriving monthly runoff series in data - scarce areas. Background Art

[0002] Runoff series are an important basis for determining the scale and engineering benefits of water conservancy projects. Currently, the main methods for runoff design are the hydrological analogy method and the hydrological model method. The hydrological analogy method is based on the rainfall - runoff of a reference station. The runoff of the reference basin is compared to the design basin using rainfall. This method generally uses annual rainfall or average annual rainfall as statistical parameters for comparison, and cannot reflect the difference in monthly rainfall distribution between the reference basin and the design basin. There are many types of current hydrological models, which are basically runoff - generation and concentration models based on water balance. The calibration of current hydrological models and runoff calculation generally require various data such as rainfall, evaporation, runoff, and vegetation conditions, with high requirements for data, and poor applicability for engineering design in areas lacking data.

[0003] With the development of communication technology and automation equipment, it is more convenient to obtain accurate hydrological data. Based on this data, the theoretical research on hydrological runoff - generation and concentration is more perfect. However, there are still few studies on runoff simulation in data - scarce areas. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for deriving monthly runoff series in data - scarce areas, so as to solve the foregoing problems existing in the prior art.

[0005] To achieve the above - mentioned purpose, the technical solution adopted by the present invention is as follows: A method for deriving monthly runoff series in data - scarce areas, including the following steps:

[0006] S1, select a reference - station basin with similar runoff - generation characteristics to the design basin;

[0007] S2, organize the precipitation data of the reference - station basin into a monthly precipitation series, and organize the runoff data of the reference station into a monthly runoff series;

[0008] S3, use the monthly precipitation series and monthly runoff series organized in S2 to fit the model parameters and determine the rainfall - runoff model of the reference - station basin;

[0009] S4, organize the rainfall data of the design basin and count it as a monthly precipitation series;

[0010] S5, use the rainfall - runoff model determined in S3, the fitted model parameters, and the monthly precipitation series in S4 to derive the monthly runoff series of the design basin.

[0011] Preferably, the reference station basin selected in S1 has similarities with the design basin in terms of underlying surface conditions, runoff generation and concentration types, and climate characteristics.

[0012] Preferably, the monthly precipitation series in S2 is the areal average precipitation series within the basin, calculated using the arithmetic mean method or the Thiessen polygon method based on rain gauges within the basin, and the synchronous series length of rainfall and runoff data is more than 10 years.

[0013] Preferably, the rainfall-runoff model of the reference station basin in S3 is:

[0014] W 蓄i =[W 蓄i-1 +(P i参 -P 损 )*α 月 *(1-k) (1)

[0015] R i月＝ [W 蓄i-1 +(P i参 -P 损 )*α 月 *k (2)

[0016] In the formula: W 蓄i , W 蓄i-1 are the end-of-month basin storage volumes in the i-th month and the (i - 1)-th month; P i参 is the precipitation in the i-th month of the reference station basin; P 损 is the monthly loss of water; α 月 is the monthly runoff coefficient; k is the monthly recession coefficient; R i月 is the monthly runoff volume.

[0017] Preferably, the method for fitting model parameters in S3 is:

[0018] S301, determine an initial value of a parameter according to the physical meaning and experience of the parameter, including W 蓄i , W 蓄i-1 , α 月 , k;

[0019] S302, calculate R i月 , determine the quantitative description model and the objective function of the fitting degree between the calculation result of R i月 and the measured flow;

[0020] S303, determine the minimum value of the objective function through an optimization method to obtain the model parameters α 月 , k, and use them as the rainfall-runoff model parameters of the design basin.

[0021] Preferably, the objective function in S302 selects the weighted root mean square error function, the sum of squared residuals function, the absolute value of residuals function, or the runoff percentage error function during the dry season. In S303, the optimization method selects the genetic algorithm or the particle swarm optimization algorithm.

[0022] Preferably, in S4, the monthly rainfall series is the average precipitation series of the design basin area, which is calculated using the arithmetic mean method or the Thiessen polygon method based on the rain gauges within the basin.

[0023] The beneficial effects of the present invention are as follows: The method for deriving the monthly runoff series in data - scarce areas provided by the present invention selects a reference station basin, organizes the rainfall - runoff series of the reference station basin, establishes a runoff - generation model for the reference station basin, fits the parameters of the runoff - generation model for the reference station basin, and uses the parameters of the runoff - generation model fitted for the reference station basin and the monthly precipitation series of the design basin to calculate the monthly runoff series of the design basin. Therefore, by using the method provided by the present invention, the monthly runoff series can be derived in areas with only monthly rainfall data. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of the method for deriving the monthly runoff series in data - scarce areas provided by the present invention.

[0025] Figure 2 It is a comparison chart of the measured and simulated processes of the present invention.

[0026] Figure 3 It is a runoff process diagram generated for the design basin of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the attached drawings and tables. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0028] As Figure 1 shown, the present invention relates to a method for deriving the monthly runoff series in data - scarce areas, including the following steps:

[0029] S1, select a reference station basin with similar runoff - generation characteristics to the design basin: Analyze the distribution of reference stations near the design basin, and select a reference station basin with similar underlying surface conditions, runoff - generation and concentration types, and climate characteristics to the design basin.

[0030] S2, organize the precipitation data of the reference station basin into a monthly precipitation series, and organize the runoff data of the reference station basin into a monthly runoff series: Collect the data of rain gauges above the hydrological station in the reference station basin, calculate the average precipitation of the reference station basin area using the arithmetic mean method or the Thiessen polygon method, and organize it into a monthly precipitation series. Organize the reference station flow data into a monthly average flow series.

[0031] S3. Use the monthly precipitation series and monthly runoff series sorted in S2 to fit the model parameters and determine the rainfall-runoff model for the reference station basin: Establish the rainfall-runoff model for the reference station basin, determine an initial parameter value based on the physical meaning and experience of the parameters, and determine the objective function that quantitatively describes the fitting degree between the model calculation result and the measured flow; Determine the minimum value of the objective function through an optimization method to determine the model parameters.

[0032] S4. Organize the rainfall data of the design basin and count it as a monthly precipitation series: Collect the data of the rain gauges in the design basin, calculate the areal average precipitation of the design basin using the arithmetic mean method or the Thiessen polygon method, and organize it into a monthly precipitation series.

[0033] S5. Use the rainfall-runoff model determined in S3, the fitted model parameters, and the monthly precipitation series in S4 to derive the monthly runoff series of the design basin: Use the runoff generation and concentration model and model parameters determined for the reference station basin, and generate the monthly runoff series using the monthly precipitation series of the design basin.

[0034] Specifically, the reference station basin selected in S1 has similarities with the design basin in terms of underlying surface conditions, runoff generation and concentration types, and climate characteristics.

[0035] Specifically, the monthly precipitation series in S2 is the areal average precipitation series within the basin, calculated using the arithmetic mean method or the Thiessen polygon method based on the rain gauges within the basin, and the synchronous series length of the rainfall and runoff data is more than 10 years.

[0036] Specifically, the rainfall-runoff model for the reference station basin in S3 is:

[0037] W 蓄i =[W 蓄i-1 +(P i参 -P 损 )*α 月 *(1-k) (1)

[0038] R i月＝ [W 蓄i-1 +(P i参 -P 损 )*α 月 *k (2)

[0039] Where: W 蓄i , W 蓄i-1 are the end-of-month basin storage volumes for the i-th month and the (i - 1)-th month; P i参 is the precipitation of the i-th month in the reference station basin; P 损 is the monthly loss of water; α 月 is the monthly runoff coefficient; k is the monthly recession coefficient; R i月is the monthly runoff.

[0040] Specifically, the method for fitting model parameters in S3 is as follows:

[0041] S301. Determine an initial parameter value according to the physical meaning and experience of the parameters, including W 蓄i 、W 蓄i-1 、α 月 、k;

[0042] S302. Determine the objective function for quantitatively describing the fitting degree between the calculation result of model R i月 and the measured flow;

[0043] S303. Determine the minimum value of the objective function through an optimization method to obtain the model parameters α 月 、k, and use them as the rainfall-runoff model parameters of the designed basin.

[0044] Specifically, the objective function selects the weighted root mean square error function, the sum of squared residuals function, the absolute value of residuals function, or the runoff percentage error function in the dry season. In S303, the optimization method selects the genetic algorithm or the particle swarm algorithm.

[0045] Specifically, the monthly rainfall series in S4 is the average surface precipitation series of the designed basin, which is calculated by the arithmetic mean method or the Thiessen polygon method according to the rain gauges in the basin. Specific embodiment

[0047] This embodiment is the design runoff calculation of the water source project for a water supply project in an industrial park in Guinea to illustrate the effect of the present invention.

[0048] The project is located in Dulup City, Boffa Province, Guinea. The proposed dam site is on the Khissilin River. There is a Bindan Hydrological Station on the adjacent Boffa River, and the observation data is from 1971 to 1985.

[0049] Step 1: Select the basin above the adjacent Bindan Hydrological Station as the reference basin.

[0050] Step 2: The precipitation in the basin above the reference station is sorted into a monthly average precipitation series using the daily precipitation data from 1971 to 1985 of the United States (NOAA Climate Prediction Center), as shown in Table 1. The daily runoff series of the Bindan Station is sorted into a monthly average flow series, as shown in Table 2.

[0051] Table 1 Precipitation in the reference basin Unit: mm

[0052]

[0053]

[0054] Table 2 Runoff Depth of Reference Basin Unit: mm

[0055] Year January February March April May June July August September October November December 1971 10 3 0 0 0 9 51 152 166 134 52 23 1972 8 2 0 0 0 27 70 143 174 138 57 20 1973 7 1 0 0 1 11 39 163 217 120 69 21 1974 7 2 0 0 0 3 64 202 189 131 78 23 1975 8 2 0 0 0 11 116 183 242 125 73 21 1976 7 2 0 0 0 34 115 160 153 175 110 31 1977 11 3 0 0 0 4 63 123 170 124 57 17 1978 5 1 0 0 1 33 141 208 176 125 72 24 1979 8 2 0 0 1 44 113 173 160 119 88 27 1980 10 2 0 0 1 12 87 148 146 88 59 22 1981 7 2 0 0 2 12 94 148 177 115 68 29 1982 15 5 1 1 1 17 64 119 136 127 62 25 1983 11 3 1 0 2 23 80 175 138 113 51 26 1984 15 5 1 0 4 35 61 109 125 96 48 25 1985 11 3 1 0 0 11 78 183 137 116 68 27

[0056] Step 3: Establish a rainfall-runoff model for the reference basin, and fit the parameters according to the rainfall and runoff data statistically analyzed in Step 2. Based on the sorted rainfall and runoff data of the reference basin, the average annual precipitation P 参 of the reference basin can be calculated as 2208 mm, and the average annual runoff depth R 参 is 656 mm. The statistical value of α 参 is 0.29. Assume values for P 损 , α 月 , k and the initial values of W 蓄i and W 蓄i-1 . Through the model, the monthly runoff of the reference basin is determined, and during the process of fitting the runoff, the statistical average annual runoff coefficient is set to 0.29. By continuously adjusting k, the error between the simulated runoff process and the measured runoff process is minimized. The value range of α 月 is [0, 1], and the value of P 损 , based on the underlying surface characteristics of the basin, is in the range of [50, 150]. Finally, when considering that the fitting runoff process matches well with the measured runoff process, P 损 is determined to be 131 mm, α 月 is 0.49, and k is 0.56. In runoff design, the dry season is concerned, and in parameter fitting, the simulation effect during the dry season is emphasized. The fitting effect is shown in Figure 2 .

[0057] Step 4: The daily precipitation data of the United States (NOAA Climate Prediction Center) from 1971 to 1985 are used to organize the monthly average precipitation series of the designed basin surface precipitation series. The organized monthly precipitation series is shown in Table 3.

[0058] Table 3 Rainfall of Designed Basin Unit: mm

[0059] Year January February March April May June July August September October November December 1971 0 0 0 3 58 196 293 1133 537 248 75 20 1972 0 0 0 1 90 330 351 470 484 457 58 5 1973 0 0 0 16 166 260 727 719 591 177 87 17 1974 0 8 0 0 43 180 866 950 542 185 110 5 1975 0 0 0 14 63 265 796 883 650 413 14 5 1976 0 1 0 8 116 492 835 940 519 379 188 5 1977 0 0 0 3 41 328 890 993 450 228 0 5 1978 0 0 0 16 146 212 1025 1008 630 255 27 14 1979 0 0 0 1 43 386 672 678 434 290 20 13 1980 0 2 0 13 29 410 831 907 369 101 33 14 1981 0 0 5 6 199 234 835 730 492 234 13 7 1982 0 0 0 5 53 259 626 1060 338 312 33 5 1983 0 1 2 0 130 305 732 702 392 177 28 8 1984 0 0 0 18 159 256 424 395 296 183 93 5 1985 0 0 0 2 22 356 428 748 499 343 43 4

[0060] Step 5: Using the parameters and model determined in Step 3 and the monthly precipitation series in Step 5, generate the monthly runoff series of the designed basin, as shown in Table 4 Figure 3 .

[0061] Table 4 Runoff Depth of Designed Basin Unit: mm

[0062] Year January February March April May June July August September October November December 1971 18.1 8.0 3.5 1.5 0.7 18.0 52.3 298.0 242.4 138.8 61.1 26.9 1972 11.8 5.2 2.3 1.0 0.4 54.8 84.5 130.2 154.1 157.3 69.2 30.4 1973 13.4 5.9 2.6 1.1 10.1 39.7 181.1 240.9 232.1 114.8 50.5 22.2 1974 9.8 4.3 1.9 0.8 0.4 13.5 207.5 316.1 252.0 125.5 55.2 24.3 1975 10.7 4.7 2.1 0.9 0.4 36.9 198.8 293.9 271.7 197.0 86.7 38.1 1976 16.8 7.4 3.2 1.4 0.6 99.4 236.8 326.3 250.0 178.2 94.0 41.4 1977 18.2 8.0 3.5 1.5 0.7 54.4 232.2 338.7 236.6 130.6 57.5 25.3 1978 11.1 4.9 2.2 0.9 4.6 24.2 256.0 353.3 292.4 162.7 71.6 31.5 1979 13.9 6.1 2.7 1.2 0.5 70.3 179.3 228.9 183.8 124.4 54.7 24.1 1980 10.6 4.7 2.1 0.9 0.4 76.7 225.8 312.3 202.8 89.2 39.3 17.3 1981 7.6 3.3 1.5 0.6 19.1 36.6 209.3 256.6 212.0 121.6 53.5 23.5 1982 10.4 4.6 2.0 0.9 0.4 35.2 151.5 321.5 198.3 136.9 60.3 26.5 1983 11.7 5.1 2.3 1.0 0.4 48.1 186.1 238.6 176.5 90.2 39.7 17.5 1984 7.7 3.4 1.5 0.7 8.0 37.7 97.1 115.0 96.0 56.6 24.9 10.9 1985 4.8 2.1 0.9 0.4 0.2 61.8 108.8 217.1 196.6 144.6 63.6 28.0

[0063] Therefore, by using the method provided by the present invention, the monthly runoff series of the design basin can be derived in the case of less data in the design basin and no runoff data.

[0064] By adopting the above technical solutions disclosed by the present invention, the present invention selects the reference station basin, collates the rainfall-runoff series of the reference station basin, establishes the runoff generation model of the reference station basin, fits the parameters of the runoff generation model of the reference station basin, and uses the parameters of the runoff generation model fitted by the reference station basin and the monthly precipitation series of the design basin to calculate the monthly runoff series of the design basin. Therefore, the method provided by the present invention can derive the monthly runoff series in areas with only monthly rainfall data.

[0065] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for deriving the monthly runoff series in data - scarce areas, characterized in that, it includes the following steps: S1. Select a reference - station basin similar to the design basin in terms of runoff - generation characteristics; S2. Organize the precipitation data of the reference - station basin into a monthly precipitation series, and organize the runoff data of the reference - station basin into a monthly runoff series; S3. Use the monthly precipitation series and monthly runoff series organized in S2 to fit the model parameters and determine the rainfall - runoff model of the reference - station basin; The rainfall - runoff model of the reference - station basin is: W 蓄i = [W 蓄i-1 + (P i参 - P 损 ) * α 月 * (1 - k) (1) R i月＝ [ W 蓄i-1 +(P i参 -P 损 )*α 月 * k (2) Where: W 蓄i and W 蓄i-1 are the water storage in the basin at the end of the i-th month and the (i - 1)-th month respectively; P i参 is the precipitation in the i-th month in the basin of the reference station; P 损 is the monthly loss of water; α 月 is the monthly runoff coefficient; k is the monthly recession coefficient; R i月 is the monthly runoff; The method for fitting the model parameters is: S301. Determine an initial parameter value based on the physical meaning of the parameters and experience, including W 蓄i 、W 蓄i-1 、α 月 、k; S302, calculate R i月 , determine the quantitative description model and establish R i月 The objective function of the fitting degree between the calculation result and the measured flow rate; S303. Determine the minimum value of the objective function through an optimization method to obtain the model parameters α 月 and k, and use them as the rainfall-runoff model parameters for the designed basin; Among them, in S302, the objective function is selected from the weighted root - mean - square error function during the dry season, the sum - of - squared - residuals function, the absolute - value - of - residuals function, or the runoff percentage error function; in S303, the optimization method is selected from the genetic algorithm or the particle - swarm algorithm; S4. Organize the rainfall data of the design basin and count it as a monthly precipitation series; S5. Use the rainfall - runoff model determined in S3, the fitted model parameters, and the monthly precipitation series in S4 to derive the monthly runoff series of the design basin.

2. The method for deriving the monthly runoff series in data - scarce areas according to claim 1, characterized in that, the reference - station basin selected in S1 has similarities with the design basin in terms of underlying - surface conditions, runoff - generation and - concentration types, and climate characteristics.

3. The method for deriving the monthly runoff series in data - scarce areas according to claim 1, characterized in that, the monthly precipitation series in S2 is the areal - average precipitation series within the basin, calculated using the arithmetic - mean method or the Thiessen - polygon method based on the rain - gauge stations within the basin, and the synchronous series length of rainfall and runoff data is more than 10 years.

4. The method for deriving the monthly runoff series in data - scarce areas according to claim 1, characterized in that, the monthly rainfall series in S4 is the areal - average precipitation series of the design basin, calculated using the arithmetic - mean method or the Thiessen - polygon method based on the rain - gauge stations within the basin.

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